JPH07104335B2 - Method for detecting abnormal water quality by fish - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial application] The present invention relates to image monitoring of a plurality of living organisms in influent water and treated water of a purification plant or a sewage treatment plant, and the behavior of each individual fish. It relates to a method of accurately grasping.

[Conventional technology]

In order to determine whether or not toxic substances have been mixed in raw water at water purification plants, etc., some raw water or purified water is introduced to a tank, and fish such as crucian carp, carp, dace, tanago, oikawa and gold are raised in this tank. is doing. Similarly, fish may be bred to monitor the treated water, effluent water, river water, and lakes of sewage treatment plants for the presence of toxic substances in the water. When a poisonous substance is mixed in water, the fish behave abnormally or die, so this is visually monitored. However, since it relies on visual inspection and cannot be detected when a person is not monitoring it, automatic monitoring has been desired.

As an automatic method of monitoring fish, a method of photographing fish in an aquarium with an industrial TV camera from the top of the aquarium and processing the image (Reference: 36th National Waterworks Research Conference, Lectures p.464-466) is considered. ing. This method uses a camera to observe the phenomenon in which a fish that has died due to abnormal water quality floats up on the water surface with its abdomen up.
As an "independent bright spot of a certain size or more", it is confirmed and an alarm of abnormal water quality is issued. In addition, JP-A-61-46
294 discloses a method of monitoring the behavioral patterns of multiple organisms to monitor water quality. The disclosed technology describes that temperature and water quality are measured by a water quality sensor, and normality / abnormality of an action pattern is determined with reference to the measured values. It is described that the action pattern also includes speed and position. However, whenever an action pattern is simply analyzed using image technology, such an idea is known in the art, and how to specifically detect or evaluate the velocity and position of multiple organisms. Is not disclosed, so it is difficult to implement.

[Problems to be solved by the invention]

Of the above-mentioned conventional techniques, the method of detecting a dead fish is
However, there was a problem that the abnormal water quality could not be detected until the fish died and floated up. Secondly, if the fish died at the bottom of the aquarium and did not float up, no measures were taken. Further, JP-A-61-46294 does not disclose a specific method for detecting abnormal water quality, which makes it difficult to implement. Furthermore, it is difficult to distinguish between disease and abnormal water quality based on the behavior of one test fish.

An object of the present invention is to provide a method capable of accurately detecting the behavioral states of a plurality of fishes.

[Means for solving problems]

The present invention relates to an aquarium for breeding a plurality of fishes for detecting inflow of toxic substances into water, an imaging device for converting image information of the fishes into an electric signal at regular time intervals, and an illumination for illuminating the fishes in the aquarium. Image monitoring provided with a device, a binarizing unit for extracting the fish as a binary image from a multi-valued image captured by the image capturing unit, a unit for identifying the position of the fish by individual, and a unit for calculating the position of the fish. A device is provided, and the vertical coordinates in which fish are expected to be present in abnormal water quality and the number of fish bodies at that position are set in advance, and the vertical coordinates of fish and the number of fish bodies at that position are set by the image monitoring device. It is determined that the water quality is abnormal when the actual measured value of the number of fish bodies in the vertical coordinate where fish are expected to be present when the water quality is abnormal is greater than the preset value. Characteristic water quality inspection Lies in the way.

[Action]

When the water quality is abnormal, the fish behaves as if it has its mouth raised to the surface, called nose lift. By sequentially detecting the position of the fish in the aquarium for each individual, this abnormal behavior can be accurately grasped,
Effectively evaluate the behavioral status of fish.

Example An example will be described below with reference to the drawings.

The configuration of the embodiment will be described with reference to FIG.

The test water is supplied to the water tank 10 by a water supply pipe 11 and a water supply pump 12. The water introduced into the water tank 10 is drained by the drain pipe 13. In the aquarium 10, there is a breeding space 19 partitioned by partition plates 18A and 18B such as wire nets and perforated plates, where fish 14
Raise A, 14B, 14C. In the present embodiment, the case where there are three fish will be described, but the same embodiment can be applied to the case where there are more fish. The lighting devices 15A and 15B illuminate the fish 14 in the aquarium 10. A translucent plate 16 made of a translucent material such as frosted glass or paper is provided between the lighting devices 15A and 15B and the water tank 10. Lighting equipment
The semitransparent plate 16 scatters the light upon receiving the light from 15A and 15B, and the light emitted from the entire semitransparent plate 16 illuminates the aquarium 10. Lighting equipment
An imaging device 20 such as an industrial television camera (ITV) is arranged on the opposite side of the water tank 10 as viewed from 15A and 15B. That is, the imaging device 20 images the light emitted from the illumination devices 15A and 15B and passing through the semitransparent plate 16. Here, the imaging device 20 images the breeding space 19. Further, in order to prevent fish from coming to the surface of the water due to lack of dissolved oxygen in water, an aeration device 17 is provided in the water tank.

The signal of the imaging device 20 is guided to the image monitoring device 30. A detailed description of the configuration and operation of the image monitoring device 30 will be given later. The function of the image monitoring device 30 will be briefly described. In the image monitoring device 30, first, captured images are captured at preset time intervals h, the fish body is image-recognized, and the center of gravity of the fish body is calculated. The center of gravity of the fish is sequentially calculated for each time interval h, and the result is stored in the memory. Based on this memory information, a statistical pattern of the position (center of gravity) of the fish at a preset measurement time T is calculated, the behavior of the fish 14 is monitored, and an alarm is issued in the case of abnormality based on this monitoring result. Emitted from device 70.

The monitor TV 50 displays the captured image. The image monitor 60 receives the signal from the image monitoring device 30 and displays the image recognition result.

Next, the configuration of the image monitoring device 30 will be described in detail. Timer
31S outputs a trigger signal to the A / D converter 32 at each time interval h which is initialized. The A / D converter 32 receives the image signal output from the imaging device 20 in synchronization with this trigger signal, converts the analog signal into a digital value, and stores it in the multi-valued image memory 32M. The luminance frequency distribution calculation circuit 33 receives the signal of the multi-valued image memory 32M and calculates the luminance frequency distribution (histogram) of the multi-valued image. Here, the luminance frequency distribution is
It represents the frequency of each value (luminance) of the multi-valued image. Threshold value determination circuit 34
Receives the calculation result of the luminance frequency distribution, receives the signal of the fish body area setting circuit 34S, and determines the binarization threshold value based on both signals. The binarization circuit 35 receives the signal of the multi-valued image memory 32A and the signal of the threshold value determination circuit 34 and stores it in the binarization memory 35M. In the image numbering circuit 36, the binarized fish 14A,
The 14B and 14C parts are numbered in descending order of area. The center of gravity calculating circuit 37 calculates the center of gravity of the binarized fish portion in numerical order. Overlap number calculation circuit 38
Then, input the total number N of fish from the fish number setting circuit 38S,
The number P of overlapping fishes is calculated from the total number m which is numbered. This value is expressed by the following equation.

P = N−m (1) In the overlap distribution circuit 39, the number of overlaps P calculated by the equation (1)
Are distributed in order of large area fish. Abnormal position determination circuit
Based on the abnormality setting circuit 40S and the position of the center of gravity of the fish, 40 determines abnormal water quality when the number of fish near the water surface is greater than the set number of fish, and outputs an alarm signal to the alarm device 70.

Next, the operation of the image monitoring device 30 will be described in detail.

The timer 31T outputs an A / D conversion trigger signal to the A / D converter 32 at each time interval h. This h is about 0.1 second to 2 seconds, and the following image processing is executed at this time interval.

The A / D converter 32 converts the multi-valued image signal from the imaging device 20 from an analog value to a digital value in synchronization with the trigger signal output from the timer 31T, and converts the digital multi-valued image signal into a multi-valued image memory 32M. Remember. Multi-valued image memory 32M has a vertical length of 25
There are 6 and 256 horizontal memory locations, and the luminance signal of the pixel corresponding to each memory location is stored as a digital value. The signal (luminance) at the i-th row and j-th column (i = 1 to 256, j = 1 to 256) of this storage location is represented as G (i, j). A / D converter 32
If is for converting an analog value into a 7-bit digital value, G (i, j) has a digital value of 128 steps. An example of a multi-valued image stored in the multi-valued image memory 32M is shown in FIG. FIG. 3 shows an image having multi-valued luminance. The luminance frequency distribution calculation circuit 33 calculates the luminance frequency distribution of the multi-valued image. The luminance frequency distribution of FIG. 3 is shown in FIG. The threshold value determining circuit 34 determines the threshold value I based on the calculation result of the luminance frequency distribution. Next, a method of setting the threshold I will be described.

FIG. 4 shows the luminance frequency distribution. In the lighting method of the present invention, a school of fish
Since 14 can be imaged as a dark object without fail, as shown in FIG. 4, when the area of the school of fish 14 is hatched (shown by hatching, this area is referred to as f), the first area appears first.
Set the threshold I ₁ of. Since the area f differs depending on the state, the minimum area is set. This threshold setting method is particularly effective when the water becomes cloudy. However, it is better to use the _second threshold I ₂ if the water is not turbid. In FIG. 4, the peak Pf represents the fish body, the peak Pb represents the background, and the portion Pe represents the gills and outlines of the fish. To extract only the fish body, use Pf
The second threshold I ₂ is set at the boundary with Pe. As shown in FIG. 4, the threshold is set to at least the brightness I _{1 in} advance,
While searching for each frequency in the direction of increasing brightness, Pf
If there is a boundary (minimum value) with Pe, select I ₂ for this brightness.

Next, the binarization circuit 35 receives the signal of the multi-valued image memory 32M and the signal I (I ₁ or I ₂ ) of the threshold value determination circuit 34 to convert the multi-valued image to 2
It is digitized and stored in the binary memory 35M. Next, the binarization circuit 3
The specific operation of 5 will be described. The binarization circuit 35 receives the brightness G (i, j) of the multi-valued image memory 32M and sets all pixels brighter than the threshold value to "0" level, and conversely sets all pixels darker than the threshold value to "1" level. Store in the binarization memory 35M. If the set of binarized signals is B (i, j), the binarization calculation is represented by the following equation.

If G (i, j) ≧ I, B (i, j) = 0 (2) If G (i, j) <I, B (i, j) = 1 (3) (2) ( By calculating the formula 3) for all pixels, the background can be set to the “0” level and the school of fish 14 can be set to the “1” level. The result of binarizing FIG. 3 is shown in FIG.
The "1" part is indicated by hatching.

The image signal assigning circuit 36 receives the signal from the binarizing memory 35M and assigns numbers in descending order of area. The images in FIG. 5 are numbered and recognized in descending order of area as shown in FIG. The image numbering circuit 36 can number 1 to 256 for up to 256 independent objects in one screen. Subsequently, the center-of-gravity calculation circuit 37, in the order of numbering,
The centroid of the binarized image is calculated to find the centroids of g ₁ and g ₂ . In the overlap number calculation circuit 38, the fish number setting circuit 38
The total number m of numbered animals is subtracted from the number N of reared fish set in S to calculate the number P of overlapping in the image. The overlapping number distribution circuit 39 distributes the overlapping numbers P in descending order of area by weighting the number of areas. In Figure 6,
There is only one object showing the barycentric coordinates of g ₁ and g ₂ , but the overlapping number P is assigned to g ₁ from the area (S ₁ > S ₂ ) and shows the barycenter of g _1. Two objects are recognized.

The abnormal position determination circuit 40 receives from the abnormality setting circuit 40S the vertical direction coordinate L where the fish is expected to be in abnormal water quality and the number of fish bodies at that position, and compares them with the calculated center of gravity and the number of fish bodies. When more fish than the set number of fish are present near the coordinate L, it is determined to be abnormal, and a signal is output to the alarm device 70.

The position of the fish when the water quality is abnormal, which is set by the abnormality setting circuit 40S, is determined by the nose lifting action caused by the fish due to the abnormal water quality. Since the nose raising action is performed near the water surface of the aquarium,
The value near the water surface is the position of the fish when the water quality is abnormal.

〔The invention's effect〕

According to the present invention, it is possible to calculate the positions of a plurality of organisms in an aquarium and to grasp the number of individuals within a set range. There is an effect that more advanced and accurate water quality monitoring can be carried out from the ratio of the fish representing the above to the total number of breeding.

[Brief description of drawings]

FIG. 1 is an explanatory view of an embodiment of the present invention, FIG. 2 is a detailed explanatory view of an image processing apparatus in the embodiment, FIG. 3 is a multi-valued image view of a group of a plurality of fish, and FIG. 4 is a luminance frequency distribution. FIG. 5 is a binary image diagram, and FIG. 6 is a diagram showing numbering of binary images. 10 …… water tank, 14 …… fish, 20 …… imaging device, 32 …… A / D converter, 35 …… binarization circuit, 36 …… image numbering circuit, 38
...... Overlap number calculation circuit, 40 …… Abnormal position determination circuit, 50 ・ ・ ・
… Monitor TV, 60… Image monitor, 70… Alarm device.

Front page continuation (72) Inventor Naoki Hara 5-2-1 Omika-cho, Hitachi City, Ibaraki Hitachi Ltd. Omika Factory, Ltd. (72) Inventor Mikio Yoda 5-2-1 Omika-cho, Hitachi City, Ibaraki Prefecture Incorporated company Hitachi Ltd. Omika Plant (72) Inventor Kenji Baba 4026 Kuji Town, Hitachi City, Ibaraki Prefecture Hitate Manufacturing Co., Ltd.Hitachi Laboratory Ltd. (72) Inventor Kazuo Yahagi 4026 Kuji Town, Hitachi City Ibaraki Prefecture Hitachi, Ltd. (56) References JP-A-62-83663 (JP, A) JP-A-62-80557 (JP, A) Actual development 61-19765 (JP, U)

Claims (1)

[Claims] 1. An aquarium for breeding a plurality of fishes for detecting inflow of toxic substances in water, an imaging device for converting image information of the fishes into an electric signal at a constant time interval, and illuminating the fishes in the aquarium. An image including an illuminating device, a binarizing means for extracting the fish as a binary image from a multi-valued image picked up by the image pickup device, a means for individually identifying the position of the fish, and a means for calculating the position of the fish A monitoring device is provided, and the vertical coordinates in which fish are expected to be present in abnormal water quality and the number of fish bodies at that position are set in advance, and the vertical coordinates of the fish and the fish bodies at that position are set by the image monitoring device. Number and compare it with the preset value, and determine that the water quality is abnormal when the actual measured value of the number of fish in the vertical coordinate where fish are expected to be in abnormal water quality is greater than the preset value. According to the fish characterized by Method of detecting the quality abnormality.